中国碳交易政策扩散的影响因素、路径差异与减碳效果研究——基于省域数据的实证分析

碳交易市场的建设有助于实现全球碳平衡,而碳交易政策扩散对于促进中国碳交易市场的持续健康发展有着重要的现实意义。在我国碳交易市场建设不断深化的情境下,有必要识别省域碳交易政策扩散的多维影响要素,检验不同扩散路径下的政策效果差异,总结政策扩散经验。文章基于省域面板数据,首先运用事件史分析法,通过Cox比例风险模型发现,能源政策的落实、地方政府的综合服务能力和社会创新能力是碳交易政策扩散的关键驱动要素;其次,利用合成控制法进一步检验,发现主动扩散地区的减排效果弱于试点扩散地区,试点扩散地区对主动扩散地区的激励和带动作用有限,试点成果尚未得到有效学习和复制。为此,在我国统一碳交易市场的建设过程中,应强化中央统筹协调与地方相关举措之间的协同配合,依托有力的政策驱动激发我国碳交易制度活力,提升碳减排效果,形成路径清晰、梯度有序的政策扩散机制,以稳步实现2030“碳达峰”、2060“碳中和”的目标。     

计划生育利益导向政策对家庭发展的影响效应分析

我国计划生育利益导向政策可大致分为早期主要控制人口数量的利益导向政策和当前倾向于综合治理的利益导向政策两个时期。本文在回顾计划生育利益导向政策的演变历程的基础上,利用1991-2010年我国29个省的面板数据实证分析了计划生育利益导向政策对家庭发展的影响,研究发现,相比较于以控制人口数量为主的计划生育利益导向政策,倾向于综合治理的计划生育利益导向政策对生育水平的影响效应更强,并且更有利于家庭经济状况的改善。在倾向于综合治理的计划生育利益导向政策的实施下,家庭会调整发展策略,通过风险外部转移和加强人力资本投资等多种方式,缓冲由于子女数量减少导致的不确定风险增加。     

浅谈业主对工程造价的控制

从业主角度出发 ,从五个方面下手 ,提出如何有效控制工程造价。指出设计阶段是关键 ,招投标是基础 ,严格把关竣工决算审核 ,并针对工程中的实际情况提出个人的看法和可实施的解决方案 ,供工程管理人员参考。     

企业内部控制中存在的问题与对策

内部控制是企业经营活动中强化内部会计监督,进行自我调节和自我约束的内在机制。我国企业在内部控制环境、会计责权控制和内部审计方面存在一些问题,必须建立健全企业内部控制机制。推动企业内部控制目标的实现,实现企业价值最大化。     

西双版纳:民族文化多元性与生物多样性的协调统一

云南省西双版纳地区是一个民族文化多元性和生物资源多样性特征十分突出的地区 ,在西双版纳地区的现代社会发展中 ,要十分珍惜和有效保护好丰富的民族文化和多样性的生物资源与生态环境。     

The impact of learning opportunities and decision authority on occupational health

In an investigation of 418 employees in the Norwegian Postal Service, employees with high learning opportunities and high decision authority were found to be better off on psychological functioning, health and organizational outcome variables than employees with low scores on these variables. Decision authority and learning opportunities had specific and independent impact on subjective health, psychological functioning, coping style and organizational outcome variables. There were, however, also interaction effects between demands, learning opportunities, and decision authority on subjective health. Learning opportunities and decision authority were operationalized with a questionnaire, supplemented with questions on the opportunities to learn skills beyond the present job situation. It is suggested that this is a particularly important dimension for coping with the present day rapid changes in working life, where the objective for many workers will be to broaden their repertoire and competence to increase their flexibility in the labour market.     

The multivariate alpha-power model

The main object of this paper is to propose a multivariate extension to the alpha-power model which is an alternative to the multivariate skew-normal model (Arellano-Valle and Azzalini, 2008). It also extends the power-normal model discussed in Gupta and Gupta (2008) by making it more flexible. Inference is dealt with by using the likelihood approach and a pseudo-likelihood approach based on conditional distributions which, although slightly less efficient, is simpler to implement. An application to a real data set is used to demonstrate the usefulness of the extension.     

The Gaussian Mixture Dynamic Conditional Correlation Model: Parameter Estimation,Value at Risk Calculation,and Portfolio Selection

A multivariate generalized autoregressive conditional heteroscedasticity model with dynamic conditional correlations is proposed, in which the individual conditional volatilities follow exponential generalized autoregressive conditional heteroscedasticity models and the standardized innovations follow a mixture of Gaussian distributions. Inference on the model parameters and prediction of future volatilities are addressed by both maximum likelihood and Bayesian estimation methods. Estimation of the Value at Risk of a given portfolio and selection of optimal portfolios under the proposed specification are addressed. The good performance of the proposed methodology is illustrated via Monte Carlo experiments and the analysis of the daily closing prices of the Dow Jones and NASDAQ indexes.     

The Job Demands-Job Control Model and absence behaviour: results of a 3-year longitudinal study

Empirical results of earlier studies only marginally supported the relevance of Karasek's Job Demands-Job Control Model for absence behaviour. Since longitudinal studies with respect to these relations were largely lacking, a four-wave panel study was carried out using data from 1755 male employees of a technical maintenance firm in the public sector. Job demands, job control, physical working conditions, and the employee's age, education, and health were measured in one year and absenteeism in the same year and in the next 3 years. Data were analysed with linear regression and Poisson regression techniques. The Poisson regression technique was superior to the linear regression technique in explaining absence. Age, health and prior absence were the best predictors of later absence behaviour. With respect to the Job Demands-Job Control Model, the main findings of the study were (1) that job control was significantly associated with a low number of simultaneous and later absence days, and (2) that, contrary to expectations, job demands were also related to a low number of simultaneous and later absence days. These results hold when age, health, education, prior absence, and working conditions are controlled for. Job control and job demands did not predict later absence frequency. In the discussion it is suggested that a high level of job demands may not only be harmful for the well-being of employees but also work as 'a pressure to attend'.     

The Extremal Dependence Measure and Asymptotic Independence

Abstract

Extremal dependence analysis assesses the tendency of large values of components of a random vector to occur simultaneously. This kind of dependence information can be qualitatively different than what is given by correlation which averages over the total body of the joint distribution. Also, correlation may be completely inappropriate for heavy tailed data. We study the extremal dependence measure (EDM), a measure of the tendency of large values of components of a random vector to occur simultaneously and show consistency of an estimator of the EDM. We also show asymptotic normality of an idealized estimator in a restricted case of multivariate regular variation where scaling functions do not have to be estimated.